Chemometric Analysis Evidencing the Variability in the Composition of Essential Oils in 10 Salvia Species from Different Taxonomic Sections or Phylogenetic Clades.

Essential oil (EO) of Salvia spp. has been widely used for culinary purposes and in perfumery and cosmetics, as well as having beneficial effects on human health. The present study aimed to investigate the quantitative and qualitative variations in EOs in wild-growing and cultivated pairs of samples from members in four Salvia sections or three clades, namely S. argentea L. (Sect. Aethiopis; Clade I-C), S. ringens Sm. (Sect. Eusphace; Clade I-D), S. verticillata L. (Sect. Hemisphace; Clade I-B), S. amplexicaulis Lam., and S. pratensis L. (Sect. Plethiosphace; Clade I-C). Furthermore, the natural variability in EO composition due to different genotypes adapted in different geographical and environmental conditions was examined by employing members of three Salvia sections or two phylogenetic clades, namely S. sclarea L. (six samples; Sect. Aethiopis or Clade I-C), S. ringens (three samples; Sect. Eusphace or Clade I-D), and S. amplexicaulis (five samples; Sect. Plethiosphace or Clade I-C). We also investigated the EO composition of four wild-growing species of two Salvia sections, i.e., S. aethiopis L., S. candidissima Vahl, and S. teddii of Sect. Aethiopis, as well as the cultivated material of S. virgata Jacq. (Sect. Plethiosphace), all belonging to Clade I-C. The EO composition of the Greek endemic S. teddii is presented herein only for the first time. Taken together, the findings of previous studies are summarized and critically discussed with the obtained results. Chemometric analysis (PCA, HCA, and clustered heat map) was used to identify the sample relationships based on their chemical classes, resulting in the classification of two distinct groups. These can be further explored in assistance of classical or modern taxonomic Salvia studies.

Modification of heat-related effects on mortality by air pollution concentration, at small-area level, in the Attica prefecture, Greece.

BACKGROUND: The independent effects of short-term exposure to increased air temperature and air pollution on mortality are well-documented. There is some evidence indicating that elevated concentrations of air pollutants may lead to increased heat-related mortality, but this evidence is not consistent. Most of these effects have been documented through time-series studies using city-wide data, rather than at a finer spatial level. In our study, we examined the possible modification of the heat effects on total and cause-specific mortality by air pollution at municipality level in the Attica region, Greece, during the warm period of the years 2000 to 2016. METHODS: A municipality-specific over-dispersed Poisson regression model during the warm season (May-September) was used to investigate the heat effects on mortality and their modification by air pollution. We used the two-day average of the daily mean temperature and daily mean PM10, NO2 and 8 hour-max ozone (O3), derived from models, in each municipality as exposures. A bivariate tensor smoother was applied for temperature and each pollutant alternatively, by municipality. Α random-effects meta-analysis was used to obtain pooled estimates of the heat effects at different pollution levels. Heterogeneity of the between-levels differences of the heat effects was evaluated with a Q-test. RESULTS: A rise in mean temperature from the 75th to the 99th percentile of the municipality-specific temperature distribution resulted in an increase in total mortality of 12.4% (95% Confidence Interval (CI):7.76-17.24) on low PM10 days, and 21.25% (95% CI: 17.83-24.76) on high PM10 days. The increase on mortality was 10.09% (95% CI: - 5.62- 28.41) on low ozone days, and 14.95% (95% CI: 10.79-19.27) on high ozone days. For cause-specific mortality an increasing trend of the heat effects with increasing PM10 and ozone levels was also observed. An inconsistent pattern was observed for the modification of the heat effects by NO2, with higher heat effects estimated in the lower level of the pollutant. CONCLUSIONS: Our results support the evidence of elevated heat effects on mortality at higher levels of PM10 and 8 h max O3. Under climate change, any policy targeted at lowering air pollution levels will yield significant public health benefits.

Effects of short-term air pollution exposure on symptoms development in the course of idiopathic pulmonary fibrosis.

BACKGROUND: Lately a potential detrimental effect of air pollution to idiopathic pulmonary fibrosis emerged. We aimed to assess the effects of short-term air pollution exposure to the clinical course of IPF. RESEARCH DESIGN AND METHODS: IPF patients were followed intensively for four nonconsecutive study periods between 13 July 2020 and 5 September 2021. Short-term exposure to O3, NO2 and PM10 concentrations was estimated using spatio-temporal land use regression models. Associations among symptoms, lung function, oxygen saturation, and short-term personal air pollutant exposure were assessed through multiple mixed effects logistic regression models. RESULTS: Data for up to 24 IPF patients (mean age: 72.2 ± 7.6 years) were analyzed. We detected positive significant associations between cough and a 10 µg/m3 increase in same day mean level of NO2 (OR = 1.59, 95%CI: 1.00-2.53), PM10 (OR = 2.42, 95%CI: 1.54-3.79), and O3 (OR = 1.63, 95%CI: 1.14-2.32). A 10 µg/m3 increase in same day mean level of NO2 was also associated with the risk of appearance of wheezing (OR = 3.01, 95%CI: 1.00-9.04), while exposure to O3 was associated with common cold (OR = 6.30, 95%CI: 3.59-11.07). No significant associations were detected between short-term exposure to air pollutants and forced vital capacity or saturation of oxygen. CONCLUSIONS: Short-term exposure to increased concentrations of air pollutants is an independent risk factor for IPF symptoms' aggravation.

Mixtures of long-term exposure to ambient air pollution, built environment and temperature and stroke incidence across Europe.

INTRODUCTION: The complex interplay of multiple environmental factors and cardiovascular has scarcely been studied. Within the EXPANSE project, we evaluated the association between long-term exposure to multiple environmental indices and stroke incidence across Europe. METHODS: Participants from three traditional adult cohorts (Germany, Netherlands and Sweden) and four administrative cohorts (Catalonia [region Spain], Rome [city-wide], Greece and Sweden [nationwide]) were followed until incident stroke, death, migration, loss of follow-up or study end. We estimated exposures at residential addresses from different exposure domains: air pollution (nitrogen dioxide (NO2), particulate matter < 2.5 µm (PM2.5), black carbon (BC), ozone), built environment (green/blue spaces, impervious surfaces) and meteorology (seasonal mean and standard deviation of temperatures). Associations between environmental exposures and stroke were estimated in single and multiple-exposure Cox proportional hazard models, and Principal Component (PC) Analyses derived prototypes for specific exposures domains. We carried out random effects meta-analyses by cohort type. RESULTS: In over 15 million participants, increased levels of NO2 and BC were associated with increased higher stroke incidence in both cohort types. Increased Normalized Difference Vegetation Index (NDVI) was associated with a lower stroke incidence in both cohort types, whereas an increase in impervious surface was associated with an increase in stroke incidence. The first PC of the air pollution domain (PM2.5, NO2 and BC) was associated with an increase in stroke incidence. For the built environment, higher levels of NDVI and lower levels of impervious surfaces were associated with a protective effect [%change in HR per 1 unit = -2.0 (95 %CI, -5.9;2.0) and -1.1(95 %CI, -2.0; -0.3) for traditional adult and administrative cohorts, respectively]. No clear patterns were observed for distance to blue spaces or temperature parameters. CONCLUSIONS: We observed increased HRs for stroke with exposure to PM2.5, NO2 and BC, lower levels of greenness and higher impervious surface in single and combined exposure models.

Sideritis L. essential oils: A systematic review.

Essential oils are extensively used in the food, cosmetic, perfume, pharmaceutical, and agrochemical industries due to their aroma and pharmacological properties. The Lamiaceae family is mainly represented by widely well-known medicinal and aromatic plants that produce essential oil. Over the years, Sideritis L. essential oils have attracted great interest due to their chemical variability among the different taxa and their pharmacological activities. In-depth research of previously published literature was performed on electronic databases with several key search words for the collection of the available data and a total of 128 scientific studies were used since 1983. To date, 155 accepted Sideritis samples have been studied originating from 15 countries and more than 250 compounds have been reported in 87 Sideritis taxa overall. Furthermore, antimicrobial and antioxidant effects have been the most studied pharmacological activities. This review summarizes and critically discusses the research work on the chemical composition and pharmacological activities of essential oil of the genus Sideritis based on the currently valid taxonomy. Additionally, statistical analysis is encompassed to provide a deeper comprehensive understanding of the high chemical polymorphism of Sideritis essential oils. We expect that this review will encourage researchers to investigate unexplored Sideritis taxa and will contribute to revealing uncharted scientific territory and future perspectives on these plants.

Associations between exposure to blue spaces and natural and cause-specific mortality in Greece: An ecological study.

BACKGROUND: A growing body of evidence suggests that exposure to natural environments, such as green space, may have a beneficial role in health. However, there is limited evidence regarding the effects of exposure to blue spaces and mortality. We investigated the association of exposure to blue spaces with natural and cause-specific mortality in Greece using an ecological study design METHODS: Mortality and socioeconomic data were obtained from 1,035 municipal units (MUs) from the 2011 census data. To define exposure to "blue" we used a rate of the land cover categories related to blue space from the COoRdination and INformation on the Environmental (CORINE) 2012 map per 10,000 persons in the municipal unit. We further assessed the exposure to blue space in the MUs that are located in the coastline of Greece using the distance to the coast as a proxy for proximity to blue space. the Annual PM2.5, NO2, BC and O3 concentrations for 2010 were predicted by land use regression models while the normalized difference vegetation index was used to assess greenness. We applied single and two exposure Poisson regression models accounting for spatial autocorrelation and adjusting for unemployment and lung cancer mortality rates, percentages of the population aged 25-64 with upper secondary or tertiary education attainment and of those born in Greece, and urbanicity. The analysis was conducted for the whole country and separately by varying geographical definitions. RESULTS: An interquartile range (IQR) increase of blue space per 10,000 persons was associated with decreased risk in natural mortality (Relative Risk (RR): 0.98 (95% confidence interval (CI): 0.98, 0.99), as well as in mortality due to cardiovascular causes, respiratory causes and diseases of the nervous system 0.98 (95% CI: 0.97, 0.99); 0.97 (95% CI: 0.95, 0.99); 0.94 (95% CI: 0.88, 1.00) respectively). We estimated protective associations for ischemic heart disease (IHD) mortality (RR = 0.98, 95% CI: 0.97, 1.00 per IQR); COPD mortality (RR = 0.97, 95% CI: 0.93, 1.00 per IQR) and mortality from cerebrovascular disease (RR = 0.97 (95% CI: 0.96, 0.99 per IQR). We estimated protective associations for the distance from the coast and mortality from the diseases of the nervous system (RR = 0.75, 95% CI: 0.61, 0.92, ≤1 km from the coast versus >1 km). Our results were stronger for inhabitants of the islands, the coastline and in the rural areas of Greece while the estimates were robust to co-exposure adjustment. CONCLUSIONS: We estimated statistically significant protective effects of exposure to blue space on mortality from natural, cardiovascular and respiratory causes, diseases of the nervous system, cerebrovascular and ischemic heart disease for in Greece with higher estimates in the coastline and the islands. Further research is needed to elaborate our findings.

The Impact of COVID-19 Pandemic on Surgical Treatment of Resectable Non-Small Cell Lung Cancer in Greece.

Background: The coronavirus disease (COVID-19) pandemic has posed an unprecedented challenge to health systems, and has significantly affected the healthcare of lung cancer patients. The aim of our study was to assess the impact of COVID-19 on early lung cancer patients' surgical treatment. Methods: All consecutive patients with early-stage non-small cell lung cancer eligible for surgical treatment stage I/II and resectable stage III, referred to our department during the first wave of COVID-19 between February to May 2020, were included and compared with those on the exact corresponding quarter in 2019, one year before the pandemic. Waiting time to surgical treatment, increase of tumor's size and increase on lung cancer stage were recorded and compared. All subjects were followed up for 12 months. Multiple linear and logistic regression models were applied to assess the differences in the management of the studied groups adjusting for potential confounders. Results: Sixty-one patients with early-stage lung cancer were included in the study; 28 (median age 67 years, SD: 7.1) during the pandemic and 33 (median age 67.1 years, SD: 7.5) one year earlier. A significantly longer period of waiting for treatment and an increase in tumor size were observed during the pandemic compared to before the pandemic [median time 47 days, interquartile rate (IQR): 23−100] vs. [median time 18 days, IQR: 11−23], p < 0.001. No significant differences were detected in the increase of the stage of lung cancer between the subgroups. Conclusion: The COVID-19 pandemic had a significant impact on surgical and oncological care, leading to significant delays on treatment and an increase in tumor size in early-stage lung cancer patients.

Disentangling associations between multiple environmental exposures and all-cause mortality: an analysis of European administrative and traditional cohorts.

Background: We evaluated the independent and joint effects of air pollution, land/built environment characteristics, and ambient temperature on all-cause mortality as part of the EXPANSE project. Methods: We collected data from six administrative cohorts covering Catalonia, Greece, the Netherlands, Rome, Sweden, and Switzerland and three traditional cohorts in Sweden, the Netherlands, and Germany. Participants were linked to spatial exposure estimates derived from hybrid land use regression models and satellite data for: air pollution [fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), warm season ozone (O3)], land/built environment [normalized difference vegetation index (NDVI), distance to water, impervious surfaces], and ambient temperature (the mean and standard deviation of warm and cool season temperature). We applied Cox proportional hazard models accounting for several cohort-specific individual and area-level variables. We evaluated the associations through single and multiexposure models, and interactions between exposures. The joint effects were estimated using the cumulative risk index (CRI). Cohort-specific hazard ratios (HR) were combined using random-effects meta-analyses. Results: We observed over 3.1 million deaths out of approximately 204 million person-years. In administrative cohorts, increased exposure to PM2.5, NO2, and BC was significantly associated with all-cause mortality (pooled HRs: 1.054, 1.033, and 1.032, respectively). We observed an adverse effect of increased impervious surface and mean season-specific temperature, and a protective effect of increased O3, NDVI, distance to water, and temperature variation on all-cause mortality. The effects of PM2.5 were higher in areas with lower (10th percentile) compared to higher (90th percentile) NDVI levels [pooled HRs: 1.054 (95% confidence interval (CI) 1.030-1.079) vs. 1.038 (95% CI 0.964-1.118)]. A similar pattern was observed for NO2. The CRI of air pollutants (PM2.5 or NO2) plus NDVI and mean warm season temperature resulted in a stronger effect compared to single-exposure HRs: [PM2.5 pooled HR: 1.061 (95% CI 1.021-1.102); NO2 pooled HR: 1.041 (95% CI 1.025-1.057)]. Non-significant effects of similar patterns were observed in traditional cohorts. Discussion: The findings of our study not only support the independent effects of long-term exposure to air pollution and greenness, but also highlight the increased effect when interplaying with other environmental exposures.

Development and Evaluation of Spatio-Temporal Air Pollution Exposure Models and Their Combinations in the Greater London Area, UK.

Land use regression (LUR) and dispersion/chemical transport models (D/CTMs) are frequently applied to predict exposure to air pollution concentrations at a fine scale for use in epidemiological studies. Moreover, the use of satellite aerosol optical depth data has been a key predictor especially for particulate matter pollution and when studying large populations. Within the STEAM project we present a hybrid spatio-temporal modeling framework by (a) incorporating predictions from dispersion modeling of nitrogen dioxide (NO2), ozone (O3) and particulate matter with an aerodynamic diameter equal or less than 10 µm (PM10) and less than 2.5 µm (PM2.5) into a spatio-temporal LUR model; and (b) combining the predictions LUR and dispersion modeling and additionally, only for PM2.5, from an ensemble machine learning approach using a generalized additive model (GAM). We used air pollution measurements from 2009 to 2013 from 62 fixed monitoring sites for O3, 115 for particles and up to 130 for NO2, obtained from the dense network in the Greater London Area, UK. We assessed all models following a 10-fold cross validation (10-fold CV) procedure. The hybrid models performed better compared to separate LUR models. Incorporation of the dispersion estimates in the LUR models as a predictor, improved the LUR model fit: CV-R2 increased to 0.76 from 0.71 for NO2, to 0.79 from 0.57 for PM10, to 0.81 to 0.66 for PM2.5 and to 0.75 from 0.62 for O3. The CV-R2 obtained from the hybrid GAM framework was also increased compared to separate LUR models (CV-R2 = 0.80 for NO2, 0.76 for PM10, 0.79 for PM2.5 and 0.75 for O3). Our study supports the combined use of different air pollution exposure assessment methods in a single modeling framework to improve the accuracy of spatio-temporal predictions for subsequent use in epidemiological studies.

Long-term personal air pollution exposure and risk for acute exacerbation of idiopathic pulmonary fibrosis.

BACKGROUND: Urban air pollution is involved in the progress of idiopathic pulmonary fibrosis (IPF). Its potential role on the devastating event of Acute Exacerbation of IPF (AE-IPF) needs to be clarified. This study examined the association between long-term personal air pollution exposure and AE- IPF risk taking into consideration inflammatory mediators and telomere length (TL). METHODS: All consecutive IPF-patients referred to our Hospital from October 2013-June 2019 were included. AE-IPF events were recorded and inflammatory mediators and TL measured. Long-term personal air pollution exposures were assigned to each patient retrospectively, for O3, NO2, PM2.5 [and PM10, based on geo-coded residential addresses. Logistic regression models assessed the association of air pollutants' levels with AE-IPF and inflammatory mediators adjusting for potential confounders. RESULTS: 118 IPF patients (mean age 72 ± 8.3 years) were analyzed. We detected positive significant associations between AE-IPF and a 10 µg/m3 increase in previous-year mean level of NO2 (OR = 1.52, 95%CI:1.15-2.0, p = 0.003), PM2.5 (OR = 2.21, 95%CI:1.16-4.20, p = 0.016) and PM10 (OR = 2.18, 95%CI:1.15-4.15, p = 0.017) independent of age, gender, smoking, lung function and antifibrotic treatment. Introduction of TL in all models of a subgroup of 36 patients did not change the direction of the observed associations. Finally, O3 was positively associated with %change of IL-4 (p = 0.014) whilst PM2.5, PM10 and NO2 were inversely associated with %changes of IL-4 (p = 0.003, p = 0.003, p = 0.032) and osteopontin (p = 0.013, p = 0.013, p = 0.085) respectively. CONCLUSIONS: Long-term personal exposure to increased concentrations of air pollutants is an independent risk factor of AE-IPF. Inflammatory mediators implicated in lung repair mechanisms are involved.

Spatio-temporal associations of air pollutant concentrations, GP respiratory consultations and respiratory inhaler prescriptions: a 5-year study of primary care in the borough of Lambeth, South London.

BACKGROUND: Although the associations of outdoor air pollution exposure with mortality and hospital admissions are well established, few previous studies have reported on primary care clinical and prescribing data. We assessed the associations of short and long-term pollutant exposures with General Practitioner respiratory consultations and inhaler prescriptions. METHODS: Daily primary care data, for 2009-2013, were obtained from Lambeth DataNet (LDN), an anonymised dataset containing coded data from all patients (1.2 million) registered at general practices in Lambeth, an inner-city south London borough. Counts of respiratory consultations and inhaler prescriptions by day and Lower Super Output Area (LSOA) of residence were constructed. We developed models for predicting daily PM2.5, PM10, NO2 and O3 per LSOA. We used spatio-temporal mixed effects zero inflated negative binomial models to investigate the simultaneous short- and long-term effects of exposure to pollutants on the number of events. RESULTS: The mean concentrations of NO2, PM10, PM2.5 and O3 over the study period were 50.7, 21.2, 15.6, and 49.9 µg/m3 respectively, with all pollutants except NO2 having much larger temporal rather than spatial variability. Following short-term exposure increases to PM10, NO2 and PM2.5 the number of consultations and inhaler prescriptions were found to increase, especially for PM10 exposure in children which was associated with increases in daily respiratory consultations of 3.4% and inhaler prescriptions of 0.8%, per PM10 interquartile range (IQR) increase. Associations further increased after adjustment for weekly average exposures, rising to 6.1 and 1.2%, respectively, for weekly average PM10 exposure. In contrast, a short-term increase in O3 exposure was associated with decreased number of respiratory consultations. No association was found between long-term exposures to PM10, PM2.5 and NO2 and number of respiratory consultations. Long-term exposure to NO2 was associated with an increase (8%) in preventer inhaler prescriptions only. CONCLUSIONS: We found increases in the daily number of GP respiratory consultations and inhaler prescriptions following short-term increases in exposure to NO2, PM10 and PM2.5. These associations are more pronounced in children and persist for at least a week. The association with long term exposure to NO2 and preventer inhaler prescriptions indicates likely increased chronic respiratory morbidity.

A systematic review on the association between total and cardiopulmonary mortality/morbidity or cardiovascular risk factors with long-term exposure to increased or decreased ambient temperature.

The health effects of acute exposure to temperature extremes are established; those of long-term exposure only recently received attention. We performed a systematic review to assess the associations of long-term (>3 months) exposure to higher or lower temperature on total and cardiopulmonary mortality and morbidity, screening 3455 studies and selecting 34. The studies were classified in those observing associations within a population over years with changing annual temperature indices and those comparing areas with a different climate. We also assessed the risk of bias, adapting appropriately an instrument developed by the World Health Organization for air pollution. Studies reported that annual temperature indices for extremes and variability were associated with annual increases in mortality, indicating that effects of temperature extremes cannot be attributed only to short-term mortality displacement. Studies on cardiovascular mortality indicated stronger associations with cold rather than hot temperature, whilst those on respiratory outcomes reported effects of both heat and cold but were few and used diverse health outcomes. Interactions with air pollution were not generally assessed. The few studies investigating effect modification showed stronger effects among the elderly and those socially deprived. Comparisons of health outcome prevalence between areas reported lower blood pressure and a tendency for higher obesity in populations living in warmer climates. Our review indicated interesting associations between long-term exposure to unusual temperature levels in specific areas and differences in health outcomes and cardiovascular risk factors between geographical locations with different climate, but the number of studies by design and health outcome was small. Risk of bias was identified because of the use of crude exposure assessment and inadequate adjustment for confounding. More and better designed studies, including the investigation of effect modifiers, are needed.

The role of aircraft noise annoyance and noise sensitivity in the association between aircraft noise levels and medication use: results of a pooled-analysis from seven European countries.

BACKGROUND: Few studies have considered aircraft noise annoyance and noise sensitivity in analyses of the health effects of aircraft noise, especially in relation to medication use. This study aims to investigate the moderating and mediating role of these two factors in the relationship between aircraft noise levels and medication use among 5860 residents of ten European airports included in the HYENA and DEBATS studies. METHODS: Information on aircraft noise annoyance, noise sensitivity, medication use, and demographic, socio-economic and lifestyle factors was collected during a face-to-face interview at home. Medication was coded according to the Anatomical Therapeutic Chemical (ATC) classification. Outdoor aircraft noise exposure was estimated by linking the participant's home address to noise contours using Geographical Information Systems (GIS) methods. Logistic regressions with adjustment for potential confounding factors were used. In addition, Baron and Kenny's recommendations were followed to investigate the moderating and mediating effects of aircraft noise annoyance and noise sensitivity. RESULTS: A significant association was found between aircraft noise levels at night and antihypertensive medication only in the UK (OR = 1.43, 95%CI 1.19-1.73 for a 10 dB(A)-increase in Lnight). No association was found with other medications. Aircraft noise annoyance was significantly associated with the use of antihypertensive medication (OR = 1.33, 95%CI 1.14-1.56), anxiolytics (OR = 1.48, 95%CI 1.08-2.05), hypnotics and sedatives (OR = 1.60, 95%CI 1.07-2.39), and antasthmatics (OR = 1.44, 95%CI 1.07-1.96), with no difference between countries. Noise sensitivity was significantly associated with almost all medications, with the exception of the use of antasthmatics, showing an increase in ORs with the level of noise sensitivity, with differences in ORs among countries only for the use of antihypertensive medication. The results also suggested a mediating role of aircraft noise annoyance and a modifying role of both aircraft noise annoyance and noise sensitivity in the association between aircraft noise levels and medication use. CONCLUSIONS: The present study is consistent with the results of the small number of studies available to date suggesting that both aircraft noise annoyance and noise sensitivity should be taken into account in analyses of the health effects of exposure to aircraft noise.

The role of aircraft noise annoyance and noise sensitivity in the association between aircraft noise levels and hypertension risk: Results of a pooled analysis from seven European countries.

INTRODUCTION: Many studies, including the HYENA and the DEBATS studies, showed a significant association between aircraft noise exposure and the risk of hypertension. Few studies have considered aircraft noise annoyance and noise sensitivity as factors of interest, especially in relation to hypertension risk, or as mediating or modifying factors. The present study aims 1) to investigate the risk of hypertension in relation to aircraft noise annoyance or noise sensitivity; and 2) to examine the role of modifier or mediator of these two factors in the association between aircraft noise levels and the risk of hypertension. METHODS: This study included 6,105 residents of ten European airports from the HYENA and DEBATS studies. Information on aircraft noise annoyance, noise sensitivity, and demographic, socioeconomic and lifestyle factors was collected during an interview performed at home. Participants were classified as hypertensive if they had either blood pressure levels above the WHO cut-off points or physician-diagnosed hypertension in conjunction with the use of antihypertensive medication. Outdoor aircraft noise exposure was estimated for each participant's home address. Poisson regression models with adjustment for potential confounders were used. Interactions between noise exposure and country were tested to consider possible differences between countries. RESULTS: An increase in aircraft noise levels at night was weekly but significantly associated with an increased risk of hypertension (RR = 1.03, 95% CI 1.01-1.06 for a 10-dB(A) increase in Lnight). A significant association was found between aircraft noise annoyance and hypertension risk (RR = 1.06, 95%CI 1.00-1.13 for highly annoyed people compared to those who were not highly annoyed). The risk of hypertension was slightly higher for people highly sensitive to noise compared to people with low sensitivity in the UK (RR = 1.29, 95%CI 1.05-1.59) and in France (RR = 1.11, 95%CI 0.68-1.82), but not in the other countries. The association between aircraft noise levels and the risk of hypertension was higher among highly sensitive participants (RR = 1.00, 95%CI 0.96-1.04; RR = 1.03, 95%CI 0.90-1.11; RR = 1.12, 95%CI 1.01-1.24, with a 10-dB(A) increase in Lnight for low, medium, and high sensitive people respectively) or, to a lesser extent, among highly annoyed participants (RR = 1.06, 95%CI 0.95-1.18 for a 10-dB(A) increase in Lnight among highly annoyed participants, and RR = 1.02, 95%CI 0.99-1.06 among those not highly annoyed). CONCLUSIONS: The present study confirms findings in the small number of available studies to date suggesting adverse health effects associated with aircraft noise annoyance and noise sensitivity. The findings also indicate possible modifier effects of aircraft noise annoyance and noise sensitivity in the relationship between aircraft noise levels and the risk of hypertension. However, further investigations are needed to better understand this role using specific methodology and tools related to mediation analysis and causal inference.

Comparing the performance of air pollution models for nitrogen dioxide and ozone in the context of a multilevel epidemiological analysis.

Using modeled air pollutant predictions as exposure variables in epidemiological analyses can produce bias in health effect estimation. We used statistical simulation to estimate these biases and compare different air pollution models for London. METHODS: Our simulations were based on a sample of 1,000 small geographical areas within London, United Kingdom. "True" pollutant data (daily mean nitrogen dioxide [NO2] and ozone [O3]) were simulated to include spatio-temporal variation and spatial covariance. All-cause mortality and cardiovascular hospital admissions were simulated from "true" pollution data using prespecified effect parameters for short and long-term exposure within a multilevel Poisson model. We compared: land use regression (LUR) models, dispersion models, LUR models including dispersion output as a spline (hybrid1), and generalized additive models combining splines in LUR and dispersion outputs (hybrid2). Validation datasets (model versus fixed-site monitor) were used to define simulation scenarios. RESULTS: For the LUR models, bias estimates ranged from -56% to +7% for short-term exposure and -98% to -68% for long-term exposure and for the dispersion models from -33% to -15% and -52% to +0.5%, respectively. Hybrid1 provided little if any additional benefit, but hybrid2 appeared optimal in terms of bias estimates for short-term (-17% to +11%) and long-term (-28% to +11%) exposure and in preserving coverage probability and statistical power. CONCLUSIONS: Although exposure error can produce substantial negative bias (i.e., towards the null), combining outputs from different air pollution modeling approaches may reduce bias in health effect estimation leading to improved impact evaluation of abatement policies.

The impact of measurement error in modeled ambient particles exposures on health effect estimates in multilevel analysis: A simulation study.

Various spatiotemporal models have been proposed for predicting ambient particulate exposure for inclusion in epidemiological analyses. We investigated the effect of measurement error in the prediction of particulate matter with diameter <10 µm (PM10) and <2.5 µm (PM2.5) concentrations on the estimation of health effects. METHODS: We sampled 1,000 small administrative areas in London, United Kingdom, and simulated the "true" underlying daily exposure surfaces for PM10 and PM2.5 for 2009-2013 incorporating temporal variation and spatial covariance informed by the extensive London monitoring network. We added measurement error assessed by comparing measurements at fixed sites and predictions from spatiotemporal land-use regression (LUR) models; dispersion models; models using satellite data and applying machine learning algorithms; and combinations of these methods through generalized additive models. Two health outcomes were simulated to assess whether the bias varies with the effect size. We applied multilevel Poisson regression to simultaneously model the effect of long- and short-term pollutant exposure. For each scenario, we ran 1,000 simulations to assess measurement error impact on health effect estimation. RESULTS: For long-term exposure to particles, we observed bias toward the null, except for traffic PM2.5 for which only LUR underestimated the effect. For short-term exposure, results were variable between exposure models and bias ranged from -11% (underestimate) to 20% (overestimate) for PM10 and of -20% to 17% for PM2.5. Integration of models performed best in almost all cases. CONCLUSIONS: No single exposure model performed optimally across scenarios. In most cases, measurement error resulted in attenuation of the effect estimate.

Long-term exposure to ozone and children's respiratory health: Results from the RESPOZE study.

BACKGROUND: Although there is evidence on the effects of short-term ozone (O3) exposures on children's respiratory health, few studies have reported results on the effects of long-term exposures. We report the effects of long-term exposure to O3 on respiratory health outcomes in 10-11-year old children. METHODS: We conducted a panel study in a sample of the general population of school children in two cities with high average O3 concentrations, Athens and Thessaloniki, Greece. All 186 participating students were followed up intensively for 5 weeks spreading across a school year. Data was collected through questionnaires, weekly personal O3 measurements, spirometry, FeNO and time-activity diaries. Long-term O3 exposure was assessed using fixed site measurements and modeling, calibrated for personal exposures. The associations between measured lung function parameters and lung function growth over the study period, as well as FeNO and the occurrence of symptoms with long-term O3 exposure were assessed through the application of multiple mixed effects 2-level regression models, adjusting for confounders and for short-term exposures. RESULTS: A 10 µg/m3 increase in calibrated long-term O3exposure, using measurements from fixed site monitors was associated with lower FVC and FEV1 by 17 mL (95% Confidence Interval: 5-28) and 13 mL (3-21) respectively and small decreases in lung growth: 0.008% (0.002-0.014%) for FVC and 0.006% (0.000-0.012%) in FEV1 over the study period. No association was observed with PEF, FeNO or the occurrence of symptoms. A similar pattern was observed when the exposure estimates from the dispersion models were employed. CONCLUSIONS: Our study provides evidence that long-term O3 exposure is associated with reduced lung volumes and growth.

Saliva cortisol in relation to aircraft noise exposure: pooled-analysis results from seven European countries.

BACKGROUND: Many studies have demonstrated adverse effects of exposure to aircraft noise on health. Possible biological pathways for these effects include hormonal disturbances. Few studies deal with aircraft noise effects on saliva cortisol in adults, and results are inconsistent. OBJECTIVE: We aimed to assess the effects of aircraft noise exposure on saliva cortisol levels and its variation in people living near airports. METHODS: This study focused on the 1300 residents included in the HYENA and DEBATS cross-sectional studies, with complete information on cortisol sampling. All the participants followed a similar procedure aiming to collect both a morning and an evening saliva cortisol samples. Socioeconomic and lifestyle information were obtained during a face-to-face interview. Outdoor aircraft noise exposure was estimated for each participant's home address. Associations between aircraft noise exposure and cortisol outcomes were investigated a priori for male and female separately, using linear regression models adjusted for relevant confounders. Different approaches were used to characterize cortisol levels, such as morning and evening cortisol concentrations and the absolute and relative variations between morning and evening levels. RESULTS: Statistically significant increases of evening cortisol levels were shown in women with a 10-dB(A) increase in aircraft noise exposure in terms of LAeq, 16h (exp(ß) = 1.08; CI95% = 1.00-1.16), Lden (exp(ß) = 1.09; CI95% = 1.01-1.18), Lnight (exp(ß) = 1.11; CI95% = 1.02-1.20). A statistically significant association was also found in women between a 10-dB(A) increase in terms of Lnight and the absolute variation per hour (exp(ß) = 0.90; CI95% = 0.80-1.00). Statistically significant decreases in relative variation per hour were also evidenced in women, with stronger effects with the Lnight (exp(ß) = 0.89; CI95% = 0.83-0.96) than with other noise indicators. The morning cortisol levels were unchanged whatever noise exposure indicator considered. There was no statistically significant association between aircraft noise exposure and cortisol outcomes in men. CONCLUSIONS: The results of the present study show statistically significant associations between aircraft noise exposure and evening cortisol levels and related flattening in the (absolute and relative) variations per hour in women. Further biological research is needed to deepen knowledge of the pathway between noise exposure and disturbed hormonal regulation, and specially the difference in effects between genders.

Air pollution and Parkinson's disease: A systematic review and meta-analysis up to 2018.

BACKGROUND: Recent epidemiological findings investigate effects of exposure to air pollution on neurodegenerative disease. We performed a systematic review and meta-analysis to investigate the association between air pollution exposure and Parkinson's disease (PD). METHODS: We performed an extensive literature search in PubMed and Google Scholar databases and further searched for unpublished results in conference abstracts until November 2018. We identified 102 unique studies referring to air pollution and PD, from which 15 were included in the meta-analyses. We applied random-effects models to combine risk estimates and investigated between studies heterogeneity. We assessed publication bias through plots and the Egger's test in cases of sufficient number of studies. We assessed associations accounting for multi-pollutant exposures and effect modification patterns by sex and smoking habits. RESULTS: We identified 13 reports investigating associations of PD with long-term exposure to regulated air pollutants whilst two reported associations for short-term exposure to PM2.5. The pooled relative risk (RR) for incidence of PD following an increase in long-term exposure for 10 µg/m3 in PM2.5 was 1.06 (95% Confidence Interval (CI): 0.99, 1.14) and in NO2 1.01 (95%CI: 0.98, 1.03), while for 5 ppb increase in O3 1.01 (95% CI: 1.00, 1.02) and for 1 mg/m3 in CO 1.34 (95% CI: 0.85, 2.10); the pooled RR for a hospital admission due to PD after a 10 µg/m3 increase in PM2.5 short-term exposure was 1.03 (95% CI: 1.01, 1.05). There was high heterogeneity between study-specific results for most of the analyses, attributed to different populations under study. Effects were robust to multi-pollutant adjustment while there were indications of higher particles' effects among non smokers. CONCLUSIONS: We found weak evidence for an association between air pollution, mostly originating from traffic, and PD. Although meta-analysis increases power to detect small associations in rare outcomes, further research is needed to elaborate our suggestive associations. Such results are of public health significance since population aging in developed countries is expected to increase incidence of PD.

Assessing the associations of daily respiratory symptoms and lung function in schoolchildren using an Air Quality Index for ozone: Results from the RESPOZE panel study in Athens, Greece.

BACKGROUND: Air Quality indicators or indices (AQIs) are mainly used for communicating the air pollution levels and risk to the general population. However, very few epidemiological studies have used AQIs for characterizing exposure. OBJECTIVE: In the framework of the RESPOZE panel study we evaluated the association of daily ozone AQI levels with the daily occurrence of respiratory symptoms and Peak Expiratory Flow (PEF) and compared the effects with those estimated using measurements from fixed outdoor monitoring sites, in the city of Athens, Greece. MATERIALS AND METHODS: A panel of 97 children, aged 10-11years, was followed intensively for 35days (5weeks) during the academic year 2013-14. PEF and symptoms were recorded daily by each child. Two ozone AQIs classifying the air quality into 7 categories of increasing severity, were calculated; one characterizing the whole Athens area and one the local area around the child's residence and school. Measurements from fixed sites were also used. Mixed effects models for repeated measurements were applied, adjusting for several confounders. RESULTS: Increasing ozone levels were associated with increased incidence of symptoms, but the strongest and most statistically significant associations were found with the local air quality characterization with the AQI. Specifically, an increase in AQI-local by one category was associated with 34% (95% CI: 9%, 64%) increased odds of stuffy nose. When the AQI categories were "Bad" and "Severe", an increase in the incidence of cough was observed (OR 3.05 (95% CI: 1.29, 7.22) and 6.42 (95% CI: 1.47, 28.03) respectively). We did not observe a statistically significant association between AQI and PEF. CONCLUSION: Our results show that the use of an AQI based on local conditions may be advantageous over the use of only measurements when investigating the effects of air pollution on health outcomes for improving communication of risk to the public.